Filtering data objects

ABSTRACT

A method that includes establishing a layered attribute description network according to description values of the filtering requirements; extracting description values that are in the attribute description network; establishing a mapping relationship between the filtering requirements and the attribute description network, generating a path dependency graph; performing traversal comparison between the description values included in the description information of the data object to be filtered and description values in the path dependency graph; if all description values of one description path are included in the description information of the data object to be filtered, recording the description path as a matching path of the data object to be filtered; and determining a filtering requirement that the data object to be filtered meets. The techniques combine public description values and public description sub-paths based on a path dependency graph, reduce determinations in the filtering process and reduce the time of computation.

CROSS REFERENCE TO RELATED PATENT APPLICATION

This application claims foreign priority to Chinese Patent ApplicationNo. 201510011902.X filed on 9 Jan. 2015, entitled “Method, Apparatus andElectronic Device for Filtering Data Object”, which is herebyincorporate by reference in its entirety.

TECHNICAL FIELD

The present disclosure relates to data filtering technologies, and, morespecifically, to a method for filtering data objects. The presentdisclosure also relates to an apparatus and an electronic device forfiltering data objects.

BACKGROUND

With the development of cloud computing and big data, variouscomputation models have been developed in the field of big datacomputation, which are used to perform processing and computation invarious data computing scenarios. Filtering out useful data from massuser data is more and more widely used. Especially, according to a largebatch of filtering requirements that is input at a time, target usergroups that meet each filtering requirement in the large batch offiltering requirements are filtered from the massive user data.

A conventional solution is implemented by using a Map-Reduce frameworkprogram. Map-Reduce is a software framework for parallel computation oflarge volumes of data, which may process billions of data inputs in afew hours. Basic steps of Map-Reduce include two stages: Map and Reduce.The main process of the Map stage mainly includes: (1) reading a largebatch of filtering requirements, parsing expressions included therein,establishing a correspondence relationship between the expressions andMap tables, obtaining atomic expressions related to the Map tables andperform deduplication; (2) reading, piece by piece, mass user data thatis recorded in the Map tables, and performing computation for each pieceof user data cyclically by using the atomic expressions; and (3)according to an identification (ID) of a user in user data outputtedfrom the Map tables, outputting, in the form of a list, at least one ofthe atomic expressions that the user satisfies. The main process of theReduce stage mainly includes: (1) reading a large batch of filteringrequirements, parsing expressions included therein, establishing acorrespondence relationship between the expressions and Map tables, andobtaining atomic expressions that each filtering requirement needs tosatisfy, to form an atomic expression list; (2) reading user data in theMap tables, combining user data of each user in the Map tables, andafter the combination, obtaining a plurality of atomic expressions thatusers satisfy in the Map tables to form an atomic expression list; and(3) combining the results obtained in (1) and (2) to obtain acorrespondence relationship between the users and the screening orfiltering requirements, and outputting the correspondence relationshipbetween the users and the filtering requirements.

The method for filtering data objects that is provided in the aboveconventional techniques has apparent deficiencies.

The method provided in the conventional techniques is implemented basedon the Map-Reduce framework program. After a large batch of filteringrequirements is input at a time, a quite large amount of datacomputation is required. Assuming that the number of filteringrequirements is R, an average number of expressions for each filteringrequirement is E, and the number of users is N, the total amount of datacomputation for implementing screening and classification of users isR*E*N, which is a quite large amount of computation and leads to a longtime for computation. In addition, as the number of filteringrequirements increases, data computation time required to completescreening and classification of large volumes of data increases sharply,which cannot meet service requirements of filtering large volumes ofdata.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify all key featuresor essential features of the claimed subject matter, nor is it intendedto be used alone as an aid in determining the scope of the claimedsubject matter. The term “technique(s) or technical solution(s)” forinstance, may refer to apparatus(s), system(s), method(s) and/orcomputer-readable instructions as permitted by the context above andthroughout the present disclosure.

The present disclosure provides a method for filtering data objects tosolve the problem of the method for filtering data objects in theconventional techniques, which is time-consuming and cannot meet servicerequirements of filtering a large batch of data objects. The presentdisclosure also provides an apparatus for filtering data objects, and anelectronic device.

A method for filtering data objects provided by the present disclosureincludes the following operations:

reading filtering requirements;

listing description values of the filtering requirements, andestablishing an attribute description network, wherein the attributedescription network is a layered network, each layer corresponds to oneattribute field, each attribute field has at least one descriptionvalue, and layers of the attribute description network have ahierarchical relationship from high to low levels;

reading description information of a data object to be filtered andextracting, from the description information of the data object to befiltered, at least one description value that is in the attributedescription network and that is included in the description informationof the data object to be filtered;

establishing a mapping relationship between the filtering requirementsand the attribute description network, and generating a path dependencygraph according to the mapping relationship; performing traversalcomparison between the description values included in the descriptioninformation of the data object to be filtered and description values inthe path dependency graph; and in the traversal comparison process, ifall description values of one description path are included in thedescription information of the data object to be filtered, recording thedescription path as a matching path of the data object to be filtered;and

determining, according to matching paths of the data object to befiltered, a filtering requirement that the data object to be filteredmeets.

Optionally, the operation of listing description values of the filteringrequirements and establishing an attribute description network includes:

acquiring description information included in each filteringrequirement;

classifying the description information according to attributes, whereinone corresponding attribute field is set for each attribute, and atleast one piece of description information belonging to each attributeis normalized and then is respectively used as at least one descriptionvalue under the attribute field corresponding to the attribute; and

hierarchically arranging the attribute fields, according to ahierarchical relationship from high to low levels, to form the attributedescription network, wherein each layer corresponds to one attributefield.

Optionally, the operation of hierarchically arranging the attributefields according to a hierarchical relationship from high to low levelsincludes:

acquiring the number of description values under each of the attributefields; and

hierarchically arranging, in descending order of the numbers ofdescription values under the attribute fields, the attribute fields insequence according to the hierarchical relationship from high to lowlevels.

Optionally, the operation of hierarchically arranging the attributefields according to a hierarchical relationship from high to low levelsincludes:

acquiring, according to nature of the attribute fields, attribute fieldsin which a single description value is to be selected; and

placing, on top of other attribute fields, the attribute fields in whichthe single description value is to be selected,

wherein an attribute field in which the single description value is tobe selected refers to that according to nature of the attribute field,the description values included in the attribute field are mutuallyexclusive.

Optionally, in the attribute description network, different descriptionvalues of a same layer are arranged in sequence according to apredetermined sorting criterion.

Optionally, the operation of establishing a mapping relationship betweenthe filtering requirements and the attribute description network, andgenerating a path dependency graph according to the mapping relationshipincludes:

converting each filtering requirement into a description path expressionform;

respectively generating at least one description path of eachdescription path expression;

acquiring non-duplicative description paths of the filteringrequirements to form a description path set; and

mapping the description paths in the description path set to theattribute description network to form the path dependency graph.

Optionally, the description path includes at least one description valueor includes a plurality of description values that have conjunctionrelationships; and different description values of one description pathare located at different layers in the attribute description network,and different description values are arranged in descending order oflevels of the layers at which the description values are located.

Optionally, the operation of mapping the description paths in thedescription path set to the attribute description network to form thepath dependency graph includes:

sorting the description paths based on a sorting rule that a layer at ahigher level has a higher priority and a description value appearingfirst in a same layer has a higher priority;

mapping the description paths to the attribute description network insequence according to a result of the sorting; and

combining parts that have completely identical high-layer descriptionvalues in the description paths to generate the path dependency graph.

Optionally, the high-layer description values in the path dependencygraph are completely identical, which includes that, starting downwardfrom the highest-layer description values included in the descriptionpaths, all layers have identical description values.

Optionally, after the performing traversal comparison between thedescription values included in the description information of the dataobject to be filtered and description values in the path dependencygraph, in the traversal comparison process, if the descriptioninformation of the object to be filtered does not include a particulardescription value, skipping traversal of description paths in the pathdependency graph that pass downward through the particular descriptionvalue.

Optionally, in the operation of performing traversal comparison betweenthe description values included in the description information of thedata object to be filtered and description values in the path dependencygraph, the traversal is a depth-first traversal.

Optionally, the operation of determining, according to matching paths ofthe data object to be filtered, a filtering requirement that the dataobject to be filtered meets is implemented in the following operations:

determining, according to a description path expression form of eachfiltering requirement, a description path included in each requirement;and

if any description path included in a filtering requirement is includedin the matching path of the data object to be filtered, determining thatthe data object to be filtered meets the filtering requirement.

Optionally, in the operation of determining, according to matching pathsof the data object to be filtered, a filtering requirement that the dataobject to be filtered meets, all filtering requirements that the dataobject to be filtered meets are determined.

Optionally, the method comprises classifying the data object to befiltered as different categories according to the filtering requirementsthat the data object to be filtered meets.

The present disclosure also provides an apparatus for filtering dataobjects, which includes:

a filtering requirement reading unit that reads filtering requirements;

an attribute description network establishment unit that listsdescription values of the filtering requirements, and establishes anattribute description network, wherein the attribute description networkis a layered network, each layer corresponds to one attribute field,each attribute field has at least one description value, and layers ofthe attribute description network have a hierarchical relationship fromhigh to low levels;

a data-object-to-be-filtered reading unit that reads descriptioninformation of a data object to be filtered; and extracts, from thedescription information of the data object to be filtered, at least onedescription value that is in the attribute description network and thatis included in the description information of the data object to befiltered;

a path dependency graph generating unit that establishes a mappingrelationship between the filtering requirements and the attributedescription network, and generates a path dependency graph according tothe mapping relationship;

a traversal comparison unit that performs traversal comparison betweenthe description values included in the description information of thedata object to be filtered and description values in the path dependencygraph; and in the traversal comparison process, if all descriptionvalues of one description path in the path dependency graph are includedin the description information of the data object to be filtered,records the description path as a matching path of the data object to befiltered; and determines, according to matching paths of the data objectto be filtered, a filtering requirement that the data object to befiltered meets; and

a filtering requirement determining unit that determines, according tomatching paths of the data object to be filtered, a filteringrequirement that the data object to be filtered meets.

Optionally, the attribute description network establishment unitincludes:

a description information acquiring sub-unit that acquires descriptioninformation included in each filtering requirement;

a description information classifying sub-unit that classifies thedescription information according to attributes, wherein onecorresponding attribute field is set for each attribute, and at leastone piece of description information belonging to each attribute isnormalized and then is respectively used as at least one descriptionvalue under the attribute field corresponding to the attribute; and

an attribute description network generating sub-unit that hierarchicallyarranges the attribute fields according to a hierarchical relationshipfrom high to low levels, to form the attribute description network,where each layer corresponds to one attribute field.

Optionally, the attribute description network generating sub-unitincludes:

a number-of-description-values acquiring sub-unit that acquires thenumber of description values under each of the attribute fields; and

an attribute field hierarchical-arrangement sub-unit that hierarchicallyarranges, in descending order of the numbers of description values underthe attribute fields, the attribute fields in sequence according to thehierarchical relationship from high to low levels.

Optionally, the attribute description network generating sub-unitincludes:

a single-selection attribute field acquiring sub-unit that acquires,according to nature of the attribute fields, attribute fields in which asingle description value is to be selected; and

an attribute field permutation and acquiring sub-unit that places, ontop of other attribute fields, the attribute fields in which a singledescription value is to be selected,

wherein an attribute field in which a single description value is to beselected refers to that, according to nature of the attribute field, thedescription values included in the attribute field are mutuallyexclusive.

Optionally, the attribute description network generating sub-unitincludes:

a description value sorting sub-unit that arranges different descriptionvalues of a same layer in sequence according to a predetermined sortingcriterion.

Optionally, the path dependency graph generating unit includes:

a filtering requirement conversion sub-unit that converts each filteringrequirement into a description path expression form;

a description path generating sub-unit that respectively generates atleast one description path of each description path expression;

a description path set acquiring sub-unit that acquires non-duplicativedescription paths of the filtering requirements to form a descriptionpath set; and

a path dependency graph generating sub-unit that maps the descriptionpaths in the description path set to the attribute description networkto form the path dependency graph.

Optionally, the path dependency graph generating sub-unit includes:

a description path sorting sub-unit that sorts the description pathsbased on a sorting rule that a layer at a higher level has a higherpriority and a description value appearing first in a same layer has ahigher priority;

a description path mapping sub-unit that maps the description paths tothe attribute description network in sequence according to a result ofthe sorting; and

a description path combining sub-unit that combines parts that havecompletely identical high-layer description values in the descriptionpaths to generate the path dependency graph.

The present disclosure also provides an electronic device, whichincludes:

a display;

one or more processors;

an input device; and

a memory that store computer-executable instructions, where thecomputer-executable instructions are executable by the one or moreprocessors to control the electronic device to perform the followingoperations:

reading filtering requirements by using the input device;

listing description values of the filtering requirements, andestablishing an attribute description network, wherein the attributedescription network is a layered network, each layer corresponds to oneattribute field, each attribute field has at least one descriptionvalue, and layers of the attribute description network have ahierarchical relationship from high to low levels;

reading description information of a data object to be filtered; andextracting, from the description information of the data object to befiltered, at least one description value that is in the attributedescription network and that is included in the description informationof the data object to be filtered;

establishing a mapping relationship between the filtering requirementsand the attribute description network, and generating a path dependencygraph according to the mapping relationship;

performing traversal comparison between the description values includedin the description information of the data object to be filtered anddescription values in the path dependency graph; and in the traversalcomparison process, if all description values of one description path inthe path dependency graph are included in the description information ofthe data object to be filtered, recording the description path as amatching path of the data object to be filtered; and

determining, according to matching paths of the data object to befiltered, a filtering requirement that the data object to be filteredmeets.

Optionally, the filtering requirement includes description information,the description information is classified according to attributes, onecorresponding attribute field is set for each attribute, and at leastone piece of description information belonging to each attribute isnormalized and then is respectively used as at least one descriptionvalue under the attribute field corresponding to the attribute; and inthe attribute description network, each layer corresponds to oneattribute field, and the attribute fields are hierarchically arrangedaccording to a hierarchical relationship from high to low levels.

Optionally, in the attribute description network, the attribute fieldsare hierarchically arranged, in descending order of the numbers ofdescription values under the attribute fields, according to thehierarchical relationship from high to low levels.

Optionally, in the attribute description network, attribute fields inwhich a single description value is to be selected are placed on top ofother attribute fields, where an attribute field in which a singledescription value is to be selected refers to that, according to natureof the attribute field, the description values included in the attributefield are mutually exclusive.

Optionally, in the attribute description network, different descriptionvalues of a same layer are arranged in sequence according to apredetermined sorting criterion.

Optionally, the filtering requirement is used for conversion into adescription path expression form, the description path expression isused to generate a description path, and non-duplicative descriptionpaths of the filtering requirements to form a description path set; andthe description path expression form converted from each filteringrequirement includes at least one description path.

Optionally, the description path includes at least one description valueor includes a plurality of description values that have conjunctionrelationships; and different description values of one description pathare located at different layers in the attribute description network,and different description values are arranged in descending order oflevels of the layers at which the description values are located.

Optionally, in the path dependency graph, identical parts of descriptionpaths that have completely identical high-layer description values arecombined, and branch paths towards lower layers are formed; and thathigh-layer description values are completely identical refers to that,starting downward from the highest-layer description values included inthe description paths, all layers have identical description values.

Optionally, the traversal is depth-first traversal.

Optionally, there are one or more filtering requirements that the dataobject to be filtered meets, or there is no filtering requirement thatthe data object to be filtered meets.

Optionally, the data object to be filtered is classified into differentcategories according to the filtering requirements that the data objectto be filtered meets.

A method for filtering data objects includes: reading filteringrequirements; listing description values of the filtering requirements,and establishing an attribute description network, where the attributedescription network is a layered network, each layer corresponds to oneattribute field, each attribute field has at least one descriptionvalue, and layers of the attribute description network have ahierarchical relationship from high to low levels; reading descriptioninformation of a data object to be filtered; and extracting, from thedescription information of the data object to be filtered, at least onedescription value that is in the attribute description network and thatis included in the description information of the data object to befiltered; establishing a mapping relationship between the filteringrequirements and the attribute description network, and generating apath dependency graph according to the mapping relationship; performingtraversal comparison between the description values included in thedescription information of the data object to be filtered anddescription values in the path dependency graph; in the traversalcomparison process, if all description values of one description path inthe path dependency graph are included in the description information ofthe data object to be filtered, recording the description path as amatching path of the data object to be filtered; and determining,according to matching paths of the data object to be filtered, afiltering requirement that the data object to be filtered meets.

As compared with the conventional techniques, the present disclosure hasthe following technical advantages.

In the method for filtering data objects provided by the presentdisclosure, an attribute description network is established according tofiltering requirements that are read, a mapping relationship between thefiltering requirements that are input and the attribute descriptionnetwork is established, a path dependency graph is generated accordingto the mapping relationship, traversal comparison is performed betweenthe description values included in the description information of thedata object to be filtered and description values in the path dependencygraph to obtain a matching path of the data object to be filtered, so asto obtain a filtering requirement that the data object to be filteredmeets. The method for filtering data objects combines the publicdescription values and public description sub-paths based on a pathdependency graph, reduces the amount of determinations in the filteringprocess, and reduces the time of data computation. Therefore, whenfiltering large volumes of data, much time is saved and the techniquesof the present disclosure meet service requirements of filtering largevolumes of data. In an example embodiment of the present disclosure, thecomputation time is further reduced by using hierarchical filtering andpruning.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a processing flowchart of an example method for filtering dataobjects according to a first example embodiment of the presentdisclosure;

FIG. 2 is a schematic diagram of an example attribute descriptionnetwork according to the first example embodiment of the presentdisclosure;

FIG. 3 is a schematic diagram of an example path dependency graphaccording to the first example embodiment of the present disclosure;

FIG. 4 is a schematic diagram of an example apparatus for filtering dataobjects according to a second example embodiment of the presentdisclosure; and

FIG. 5 is a schematic diagram of an example electronic device accordingto a third embodiment of the present disclosure.

DETAILED DESCRIPTION

Specific details are set forth in the following description to providean understanding of the present disclosure. However, the presentdisclosure may be implemented in various manners different from thosedescribed in this specification, and those skilled in the art may makesimilar improvements without departing from the spirit of the presentdisclosure. Therefore, the present disclosure is not limited to specificimplementations disclosed below.

A first example embodiment of the present disclosure provides an examplemethod for filtering data objects, a second example embodiment of thepresent disclosure provides an example apparatus for filtering dataobjects, and a third embodiment of the present disclosure provides anexample electronic device.

With respect to the example method for filtering data objects that isprovided in the first example embodiment of the present disclosure,refer to FIG. 1 to FIG. 3, which show processing flowcharts of theexample method for filtering data objects.

The method for filtering data objects that is provided in this exampleembodiment and operations of the method are described below withreference to FIG. 1. In addition, the order of specific operations ofthe method for filtering data objects that is provided in this exampleembodiment is as shown in FIG. 1.

In this example embodiment, it is assumed that, in an applicationscenario, a large batch of filtering requirements of a merchant is readat one time by an e-commerce platform. Target users that meet thefiltering requirements are filtered out from mass users. Certainly, themethod for filtering data objects that is provided by the presentdisclosure may also be applied to other occasions, which is not limitedherein.

At 102, filtering requirements are read.

In this embodiment, the filtering requirements refer to filteringconditions that are input by the merchant to the e-commerce platform andused to filter target users from mass users.

For example, in the e-commerce platform, if the merchant wants to filterall users whose genders are male, whose ages are under 18 years old,whose interest are sports, and whose monthly spending on goods from thestore of the merchant are less than $1000, from mass users according touser information. The gender being male, the age being under 18 yearsold, the interest being sports and the monthly spending in the storebeing less than $1000 are the filtering condition input by the merchant,that is, are the filtering requirement; in addition, user information oftarget users that the merchant wants to acquire needs to satisfy thefollowing four conditions at the same time: the gender being male, theage being under 18 years old, the interest being sports and the monthlyspending in the store being less than $1000.

It should be noted that in this example embodiment, reading thefiltering requirements may refer to reading a large batch of filteringrequirements at one time, wherein the filtering requirements includevarious description information for describing target objects.

At 104, description values of the filtering requirements are listed toestablish an attribute description network.

The attribute description network refers to a method for expressing userinformation of a user.

The attribute description network may be established according to thefollowing operations:

(1) description information included in each filtering requirement isacquired.

The description information included in the filtering requirement refersto text or image information that is used to describe the filteringrequirement.

For example, if the filtering requirements of the merchant are: thegender being male, the age being under 18 years old, the interest beingsports and the monthly spending in the store being less than $1000, thedescription information included in the filtering requirement may beexpressed as “gender=male and age<18 and interest=sports and the monthlyspending in the store <$1000”.

In this operation, the description information included in eachfiltering requirement of the large batch of filtering requirements thatare read in the foregoing operation 102 is acquired, so as to preparedata for establishing the attribute description network according to thedescription information included in each filtering requirement in thefollowing operations (2) and (3).

It should be noted that this operation may further include parsing andoptimizing the description information included in the filteringrequirements.

In this example embodiment, parsing the description information refersto performing syntax analysis of the description information to checkwhether the description information is valid, and further includesoptimizing the order in which operations included in the descriptioninformation are performed.

Optimizing the description information comprises optimizing the order inwhich operations included in the description information are performed,and specifically refers to equivalently transforming all “or” operationsincluded in the description information into one or more logicalconjunction operations.

For example, description information “(A or B) and C” that includes an“or” operation is equivalently transformed into two “and” operations: “Aand C”, and “B and C”.

In addition, optimizing the description information may further includeperforming semantic analysis and optimization for the descriptioninformation, wherein performing semantic analysis and optimization forthe description information may include: performing de-duplication ofdescription information, performing de-duplication of multiple pieces ofduplicative description information and keeping one (such as a randomone) of these pieces; and analyzing a inclusion relationship between thedescription information.

For example, for description information “(A or B) and C” anddescription information “A and B and C”, the former contains the latter,that is, target users that are filtered out according to a filteringrequirement including the description information “(A or B) and C”include all target users that are filtered out according to a filteringrequirement including the description information “A and B and C”.

In addition, the parsing and optimization of the description informationincluded in the filtering requirements may also be implemented in othermanners, which is not limited herein.

(2) The description information is classified according to attributes,wherein one corresponding attribute field is set for each attribute, andat least one piece of description information belonging to eachattribute is normalized and then is respectively used as at least onedescription value under the attribute field corresponding to theattribute.

The description information included in the filtering requirements thatis acquired in the foregoing operation (1) is classified into multiplecategories according to attributes of the description information, onecorresponding attribute field is set for each attribute, at least onepiece of description information belonging to each attribute isnormalized, and the normalized description information is respectivelyused as a description value under the attribute field corresponding tothe attribute.

For example, if the description information included in the filteringrequirement is: “gender=male and age<18 and interest=sports and themonthly spending in the store <$1000”, the description informationincluded in the filtering requirement is classified into four categoriesaccording to attributes: gender, age, interest and the monthly spendingin the store, wherein the description information belonging to theattribute “gender” is “gender=male”, the description informationbelonging to the attribute “age” is “age<18”, the descriptioninformation belonging to the attribute “interest” is “interest=sports”,and the description information belonging to the attribute “the monthlyspending in the store” is “the monthly spending in the store <$1000”.

In addition, the description information “gender=male” belonging to theattribute “gender” is normalized as “male”, and is used as a descriptionvalue under the attribute field “gender”; the description information“age<18” belonging to the attribute “age” is normalized as “<18”, and isused as a description value under the attribute field “age”; thedescription information “interest=sports” belonging to the attribute“interest” is normalized as “sports”, and is used as a description valueunder the attribute field “interest”; and the description information“the monthly spending in the store <$1000” belonging to the attribute“the monthly spending in the store” is normalized as “<$1000”, and isused as a description value under the attribute field “the monthlyspending in the store”.

(3) The attribute fields are hierarchically arranged, according to ahierarchical relationship from high to low levels, to form the attributedescription network, wherein each layer corresponds to one attributefield.

The attribute description network may be abstracted as a hierarchicalfiltering model, and filtering at a current level needs to be completedbefore the filtering proceeds to a next lower level. Therefore,attribute fields corresponding to description values with strongfiltering capacities (which filter more data than other attributefields) are placed at layers of higher levels, so as to reduce theamount of data computation, thereby speeding up the computation.

In this example embodiment, the number of description values under eachof the attribute fields that are obtained in the foregoing operation (2)is acquired. The attribute fields that are obtained in the foregoingoperation (2) are hierarchically arranged, in descending order of thenumbers of description values under the attribute fields, in sequenceaccording to the hierarchical relationship from high to low levels.Accordingly, the attribute description network is formed, in which eachlayer corresponds to one attribute field.

For example, when the attribute fields that are obtained in theforegoing operation (2) are hierarchically arranged according to thehierarchical relationship from high to low levels, the following rulemay be used:

acquiring from the attribute fields, according to nature of theattribute fields, attribute fields in which a single description valueis to be selected; and

placing, on top of other attribute fields, the attribute fields in whicha single description value is to be selected,

wherein an attribute field in which a single description value is to beselected refers to that, according to nature of the attribute field, thedescription values included in the attribute field are mutuallyexclusive. For example, the description values “male, female, unknown”under the attribute field “gender” are mutually exclusive, and for anyuser, the attribute “gender” is fixed; therefore, user information of auser contains only one of “male”, “female”, and “unknown”, and cannotcontain two or more of “male”, “female”, and “unknown”.

For a single-selection attribute field, among all description valuesincluded in the attribute field, one and only one description value istrue; while for a non-single-selection attribute field, one or moredescription values may be true, and all the description values includedin the attribute field need to be traversed during data computation,which takes more time than that required to traverse a single-selectionattribute field. Therefore, by placing the single-selection attributefield on top of other attribute fields (that is, non-single-selectionattribute fields) (such as in the hierarchical relationship), the amountof data computation required for other attribute fields after filteringis performed on the single-selection attribute field is reducedeffectively, thereby reducing the time required by computation, andimproving the performance.

In addition, it should be noted that in the attribute descriptionnetwork, different description values under an attribute fieldcorresponding to a same layer are arranged in sequence according to apredetermined sorting criterion.

To sum up, the attribute description network has the followingcharacteristics:

each layer corresponds to one attribute field, each attribute field hasat least one description value, and all layers have a hierarchicalrelationship from high to low levels;

the attribute fields are hierarchically arranged, in descending order ofthe numbers of description values, in sequence according to ahierarchical relationship from high to low levels, and the attributefield in which a single description value is to be selected is placed ontop of other attribute fields; and

different description values under an attribute field corresponding toeach layer are arranged in sequence according to a predetermined sortingcriterion.

For example, FIG. 2 is a schematic diagram of an example attributedescription network.

In addition, the foregoing operation of hierarchically arranging theattribute fields according to a hierarchical relationship from high tolow levels to form the attribute description network may also beimplemented by using other methods different from that used in thisembodiment, which is not limited herein.

At 106, description information of a data object to be filtered is read.

The description information of the data object to be filtered refers touser information of mass users in the e-commerce platform.

In this operation, description information of mass data objects to befiltered is read, and from the description information of each dataobject to be filtered, at least one description value that is in theattribute description network and that is included in the descriptioninformation is extracted.

For example, if user information of a user A is “gender=male, age<18,interest=sports, the monthly spending in the store of amerchant >$1000”, extracted description values of the user A in theattribute description network shown in FIG. 2 are: “male, <18, sports,>$1000”.

At 108, a mapping relationship between the filtering requirements andthe attribute description network is established, and a path dependencygraph is generated according to the mapping relationship.

An example implementation is as follows:

(1) Each filtering requirement is converted into a description pathexpression form.

In this operation, according to the large batch of filteringrequirements that are read in the foregoing operation 102, eachfiltering requirement in the large batch of filtering requirements isconverted into a description path expression form, and the filteringrequirement corresponds to the description path expression on aone-to-one basis.

(2) at least one description path of each description path expression isrespectively generated.

After the description path expression forms are obtained according tothe foregoing operation (1), at least one description path of eachdescription path expression is generated respectively according to thedescription path expressions.

(3) A description path set formed by non-duplicative description pathsof the filtering requirements is acquired.

After the description paths of the filtering requirements are obtainedaccording to the operation (2), duplicative description paths in a setincluding the description paths of the filtering requirements areremoved to form a description path set of the filtering requirements(that is, the large batch of filtering requirements).

The description path includes at least one description value or includesa plurality of description values that have conjunction relationships;and different description values of one description path are located atdifferent layers in the attribute description network, and differentdescription values are arranged in descending order of levels of thelayers at which the description values are located.

(4) The description paths in the description path set are mapped to theattribute description network to form the path dependency graph.

After the description path set of the filtering requirements (that is,the large batch of filtering requirements) is obtained according to theforegoing operation (3), in this operation, the description paths in thedescription path set are mapped to the attribute description network toform the path dependency graph.

An example implementation is as follows:

a. sorting, according to the description path set of the filteringrequirements (that is, the large batch of filtering requirements) thatis obtained in the foregoing (3), all the description paths in thedescription path set based on a sorting rule that a layer at a higherlevel has a higher priority and a description value appearing first in asame layer has a higher priority;

b. mapping, according to a result of the sorting of all the descriptionpath in the description path set in the foregoing step a, all thedescription path in the description path set to the attributedescription network in sequence; and

c. combining parts that have completely identical high-layer descriptionvalues in the description paths to generate the path dependency graph.

The high-layer description values are completely identical refers tothat: starting downward from the highest-layer description valuesincluded in the description paths, all layers have identical descriptionvalues.

For example, the description path set includes: a description path A anddescription path B, where the description path A is: “male and <18 andsports and <$1000”, and the description path B is: “male and <18 andsports and >$1000 and <$10000”.

The description path A and the description path B have identicalhigh-layer description values (male, <18, sports).

The high-layer description values (male, <18, sports) of the descriptionpath A and the description path B are combined to form a path dependencygraph. FIG. 3 is a schematic diagram of the example path dependencygraph.

In addition, the path dependency graph may also be implemented by usingother methods, which is not limited herein.

At 110, a traversal comparison is performed between the descriptionvalues included in the description information of the data object to befiltered and description values in the path dependency graph.

According to the description information of the mass data objects to befiltered that is read in the foregoing 106 and the path dependency graphthat is obtained in the foregoing 108, in this operation, traversalcomparison is performed between the description values included in thedescription information of the data object to be filtered anddescription values in the path dependency graph, and if all descriptionvalues of one description path are included in the descriptioninformation of the data object to be filtered, the description path isrecorded as a matching path of the data object to be filtered, so as toobtain a matching path of each data object to be filtered among the massdata objects to be filtered.

With respect to each data object to be filtered, there may be one ormore matching paths or there may be no matching path.

It should be noted that in this example embodiment, traversal comparisonis performed between the description values included in the descriptioninformation of the data object to be filtered and the description valuesin the path dependency graph by using a depth-first traversal.

An example implementation process of the depth-first traversal isdescribed below by using the path dependency graph shown in FIG. 3. Thedepth-first traversal provided in this example embodiment is describedbelow with reference to the path dependency graph shown in FIG. 3.

In the path dependency graph shown in FIG. 3, according to ahierarchical relationship from high to low and the arrangement ofdescription values in a left-to-right order, the path dependency graphincludes the following description paths in sequence:

a description path 1: “male and <18 and sports and <$1000”;

a description path 2: “male and <18 and sports and >$1000 and <$10000”;

a description path 3: “male and <18 and sports and >$10000”;

a description path 4: “male and <18 and mobile phone and <$1000”;

a description path 5: “male and <18 and mobile phone and >$1000 and<$10000”;

a description path 6: “male and <18 and mobile phone and >$10000”;

a description path 7: “male and >20 and <30 and sports and <$1000”;

a description path 8: “male and >20 and <30 and sports and >$1000 and<$10000”;

a description path 9: “male and >20 and <30 and sports and >$10000”;

a description path 10: “male and >20 and <30 and mobile phone and<$1000”;

a description path 11: “male and >20 and <30 and mobile phone and >$1000and <$10000”; and

a description path 12: “male and >20 and <30 and mobile phone and>$10000”;

For example, when traversal comparison is performed against thedescription values in the path dependency graph based on a depth-firsttraversal rule:

the description information of the data object to be filtered is x, andassuming that the description information x of the data object to befiltered includes all the description values in the path dependencygraph shown in FIG. 3, the order of comparison based on the depth-firsttraversal rule is:

“male”->“<18”->“sports”->“<$1000”->“>$1000 and<$10000”->“>$10000”->“mobile phone”->“<$1000”->“>$1000 and<$10000”->“>$10000”->“20 and <30”->“sports”->“<$1000”->“>$1000 and<$10000”->“>$10000”->“mobile phone”->“<$1000”->“>$1000 and<$10000”->“>$10000”.

The order of comparison of the depth-first traversal rule is based on anassumption, and is for the purpose of fully describing the rule for theorder when traversal is performed by using the depth-first traversal.

Generally, in the traversal comparison process, if the descriptioninformation of the object to be filtered does not include a descriptionvalue, traversal of description paths in the path dependency graph thatpass downward through the description value is skipped.

For example, in the path dependency graph shown in FIG. 3, thedescription information x of the data object to be filtered does notinclude the description value “<18” of the attribute field “age”, alldescription paths that pass through the description value “<18”(including the description path 1 to the description path 6) areignored, that is, the description path 1 to the description path 6 donot need to be traversed, and only the description path 7 to thedescription path 12 need to be traversed by using the depth-firsttraversal.

If all description values of one description path are included in thedescription information of the data object to be filtered, thedescription path is recorded as a matching path of the data object to befiltered, that is, the data object to be filtered is marked with alabel, which is a label including the matching path.

If there is one matching path for the data object to be filtered, thedata object to be filtered is marked with a label including the matchingpath.

If there are multiple (greater than or equal to 2) matching paths forthe data object to be filtered, the data object to be filtered isrespectively marked with labels including the matching paths.

If there is no matching path for the data object to be filtered, itindicates that the data object to be filtered is invalid data, and noprocessing needs to be performed.

At 112, according to matching paths of the data object to be filtered, afiltering requirement met by the data object to be filtered isdetermined.

In the foregoing operation 110, through comparison according to thedepth-first traversal algorithm, the matching path of each data objectto be filtered among the mass data objects to be filtered is obtained.In this operation, a filtering requirement met by each data object to befiltered among the mass data objects to be filtered is determinedaccording to the matching path of each data object to be filtered, whichis obtained in the foregoing operation 110.

An example implementation is as follows:

(1) According to a description path expression form of each filteringrequirement, a description path included in the filtering requirement isdetermined.

At least one description path included in each filtering requirement inthe large batch of filtering requirements is determined according to thedescription path expression form of each filtering requirement in thelarge batch of filtering requirements that is obtained in the foregoingoperation 108, and each description path belongs to at least onefiltering requirement.

(2) If any description path included in a filtering requirement isincluded in the matching path of the data object to be filtered, thedata object to be filtered is determined to meet the filteringrequirement.

According to the matching path of the data object to be filtered that isobtained in the foregoing operation 110 and according to the descriptionpath that is included in each filtering requirement and that isdetermined in the foregoing step (1), the data object to be filtered isseparately classified into categories that correspond to the filteringrequirements to which the matching path belongs, that is, the filteringrequirement that each data object to be filtered meets is obtained,wherein the number of filtering requirements that each data object to befiltered meets may be one or more, or may be zero.

The above process is repeated, until the mass data objects to befiltered that are read in the foregoing operation 106 are all classifiedinto categories corresponding to the filtering requirements.

Accordingly, a set of data objects to be filtered under the category ofeach filtering requirement in the large batch of filtering requirements,which are read in 102, is obtained.

In addition, the foregoing implementation may also be implemented byusing other methods different from that used in this example embodiment,which is not limited herein.

An example apparatus for filtering data objects that is provided in thesecond example embodiment of the present disclosure is as follows:

In the foregoing example embodiment, a method for filtering data objectsis provided; correspondingly, the present disclosure also provides anapparatus for filtering data objects.

FIG. 4 is a schematic diagram of an example apparatus for filtering dataobjects according to this embodiment. The apparatus embodiment isbasically similar to the method embodiment, and therefore is brieflydescribed. For related portions, reference may be made to thecorresponding description in the method embodiment. The apparatusembodiment described below is merely exemplary.

An apparatus 400 for filtering data objects according to the presentdisclosure may include one or more processor(s) 402 or data processingunit(s) and memory 404. The apparatus 400 may further include one ormore input/output interface(s) 406, and network interface(s) 408. Thememory 404 is an example of computer-readable media.

The memory 404 may store therein a plurality of modules or unitsincluding:

a filtering requirement reading unit 410 that reads filteringrequirements;

an attribute description network establishment unit 412 that listsdescription values of the filtering requirements, and establishes anattribute description network, wherein the attribute description networkis a layered network, each layer corresponds to one attribute field,each attribute field has at least one description value, and layers ofthe attribute description network have a hierarchical relationship fromhigh to low levels;

a data object reading unit 414 that reads description information of adata object to be filtered; and extracts, from the descriptioninformation of the data object to be filtered, at least one descriptionvalue that is in the attribute description network and that is includedin the description information of the data object to be filtered;

a path dependency graph generating unit 416 that establishes a mappingrelationship between the filtering requirements and the attributedescription network, and generates a path dependency graph according tothe mapping relationship;

a traversal comparison unit 418 that performs traversal comparisonbetween the description values included in the description informationof the data object to be filtered and description values in the pathdependency graph; in the traversal comparison process, if alldescription values of one description path in the path dependency graphare included in the description information of the data object to befiltered, records the description path as a matching path of the dataobject to be filtered; and determines, according to matching paths ofthe data object to be filtered, a filtering requirement that the dataobject to be filtered meets; and

a filtering requirement determining unit 420 that determines, accordingto matching paths of the data object to be filtered, a filteringrequirement that the data object to be filtered meets.

Optionally, the attribute description network establishment unit 412includes:

a description information acquiring sub-unit that acquires descriptioninformation included in each filtering requirement;

a description information classifying sub-unit that classifies thedescription information according to attributes, wherein onecorresponding attribute field is set for each attribute, and at leastone piece of description information belonging to each attribute isnormalized and then is respectively used as at least one descriptionvalue under the attribute field corresponding to the attribute; and

an attribute description network generating sub-unit that hierarchicallyarranges the attribute fields according to a hierarchical relationshipfrom high to low levels to form the attribute description network, whereeach layer corresponds to one attribute field.

Optionally, the attribute description network generating sub-unitincludes:

a number-of-description-values acquiring sub-unit that acquires thenumber of description values under each of the attribute fields; and

an attribute field hierarchical-arrangement sub-unit that hierarchicallyarranges, in descending order of the numbers of description values underthe attribute fields, the attribute fields in sequence according to thehierarchical relationship from high to low levels.

Optionally, the attribute description network generating sub-unitincludes:

a single-selection attribute field acquiring sub-unit that acquires,according to nature of the attribute fields, attribute fields in which asingle description value is to be selected; and

an attribute field permutation and acquiring sub-unit that places, ontop of other attribute fields, the attribute fields in which a singledescription value is to be selected,

wherein an attribute field in which a single description value is to beselected refers to that, according to nature of the attribute field, thedescription values included in the attribute field are mutuallyexclusive.

Optionally, the attribute description network generating sub-unitincludes:

a description value sorting sub-unit that arranges different descriptionvalues of a same layer in sequence according to a predetermined sortingcriterion.

Optionally, the path dependency graph generating unit 416 includes:

a filtering requirement conversion sub-unit that converts each filteringrequirement into a description path expression form;

a description path generating sub-unit that respectively generates atleast one description path of each description path expression;

a description path set acquiring sub-unit that acquires non-duplicativedescription paths of the filtering requirements to form a descriptionpath set; and

a path dependency graph generating sub-unit that maps the descriptionpaths in the description path set to the attribute description networkto form the path dependency graph.

Optionally, the path dependency graph generating sub-unit includes:

a description path sorting sub-unit that sorts the description pathsbased on a sorting rule that a layer at a higher level has a higherpriority and a description value appearing first in a same layer has ahigher priority;

a description path mapping sub-unit that maps the description paths tothe attribute description network in sequence according to a result ofthe sorting; and

a description path combining sub-unit that combines parts that havecompletely identical high-layer description values in the descriptionpaths, to generate the path dependency graph.

An example electronic device that is provided in the third embodiment ofthe present disclosure is as follows:

In the foregoing embodiments, a method for filtering data objects isprovided, and a corresponding apparatus for filtering data objects isalso provided. In addition, the present disclosure provides anelectronic device that is used to implement the method for filteringdata objects.

FIG. 5 is a schematic diagram of an example electronic device accordingto according to this embodiment. The example embodiment of theelectronic device is briefly described, and for related portions,reference may be made to the corresponding description in the foregoingmethod embodiment. The embodiment of the electronic device describedbelow is merely exemplary.

An electronic device 500 according to the present disclosure includes:

a display 502;

one or more processor(s) 504 or data processing unit(s);

an input device 506; and

one or more memories 508 that store computer-executable instructionsthat are executable by the one or more processor(s) 504 to control theelectronic device 500 to perform the following operations:

reading filtering requirements by using the input device 506;

listing description values of the filtering requirements, andestablishing an attribute description network, where the attributedescription network is a layered network, each layer corresponds to oneattribute field, each attribute field has at least one descriptionvalue, and layers of the attribute description network have ahierarchical relationship from high to low levels;

reading description information of a data object to be filtered; andextracting, from the description information of the data object to befiltered, at least one description value that is in the attributedescription network and that is included in the description informationof the data object to be filtered;

establishing a mapping relationship between the filtering requirementsand the attribute description network, and generating a path dependencygraph according to the mapping relationship;

performing traversal comparison between the description values includedin the description information of the data object to be filtered anddescription values in the path dependency graph; and, in the traversalcomparison process, if all description values of one description path inthe path dependency graph are included in the description information ofthe data object to be filtered, recording the description path as amatching path of the data object to be filtered; and

determining, according to matching paths of the data object to befiltered, a filtering requirement that the data object to be filteredmeets.

Optionally, the filtering requirement includes description information,the description information is classified according to attributes, onecorresponding attribute field is set for each attribute, and at leastone piece of description information belonging to each attribute isnormalized and then is respectively used as at least one descriptionvalue under the attribute field corresponding to the attribute; and inthe attribute description network, each layer corresponds to oneattribute field, and the attribute fields are hierarchically arrangedaccording to a hierarchical relationship from high to low levels.

Optionally, in the attribute description network, the attribute fieldsare hierarchically arranged, in descending order of the numbers ofdescription values under the attribute fields, according to thehierarchical relationship from high to low levels.

Optionally, in the attribute description network, attribute fields inwhich a single description value is to be selected are placed on top ofother attribute fields, where an attribute field in which a singledescription value is to be selected refers to that, according to natureof the attribute field, the description values included in the attributefield are mutually exclusive.

Optionally, in the attribute description network, different descriptionvalues of a same layer are arranged in sequence according to apredetermined sorting criterion.

Optionally, the filtering requirement is used for conversion into adescription path expression form, the description path expression isused to generate a description path, and non-duplicative descriptionpaths of the filtering requirements form a description path set; and thedescription path expression form converted from each filteringrequirement includes at least one description path.

Optionally, the description path includes at least one description valueor includes a plurality of description values that have conjunctionrelationships; and different description values of one description pathare located at different layers in the attribute description network,and different description values are arranged in descending order oflevels of the layers at which the description values are located.

Optionally, in the path dependency graph, identical parts of descriptionpaths that have completely identical high-layer description values arecombined to form branch paths towards lower layers; and that high-layerdescription values are completely identical refers to that: startingdownward from the highest-layer description values included in thedescription paths, all layers have identical description values.

Optionally, the traversal is depth-first traversal.

Optionally, there are one or more filtering requirements that the dataobject to be filtered meets, or there is no filtering requirement thatthe data object to be filtered meets.

Optionally, the data object to be filtered is classified into differentcategories according to the filtering requirements that the data objectto be filtered meets.

Although the present disclosure has been described above through exampleembodiments, these embodiments are not intended to limit the presentdisclosure. Various possible variations and modifications may be made bythose skilled in the art without departing from the spirit and scope ofthe present disclosure. Therefore, the protection scope of the presentdisclosure shall be subject to the scope defined by the claims of thepresent disclosure.

In a typical configuration, a computation device includes one or morecentral processing units (CPUs), input/output interfaces, networkinterfaces, and memories.

The memory may include the following forms of a computer readablemedium: a volatile memory, a random access memory (RAM) and/or anon-volatile memory, for example, a read-only memory (ROM) or flash RAM.The memory is an example of the computer readable medium.

The computer readable medium includes volatile and non-volatile, mobileand non-mobile media, and can use any method or technology to storeinformation. The information may be a computer readable instruction, adata structure, a module of a program or other data. Examples of storagemedia of the computer include, but are not limited to, a phase changememory (PRAM), a static random access memory (SRAM), a dynamic randomaccess memory (DRAM), other types of RAMs, a ROM, an electricallyerasable programmable read-only memory (EEPROM), a flash memory or othermemory technologies, a compact disk read-only memory (CD-ROM), a digitalversatile disc (DVD) or other optical storage, a cassette tape, a tapedisk storage or other magnetic storage devices, or any othernon-transmission media, which can be used for storing computeraccessible information. According to the definition herein, the computerreadable medium does not include transitory computer readable media(transitory media), for example, a modulated data signal and carrier.

As will be appreciated by those skilled in the art, the embodiments ofthe present disclosure may be embodied as a method, system, or computerprogram product. Accordingly, the present disclosure may take the formof an entirely hardware embodiment, or an entirely software embodiment,or an embodiment combining software and hardware aspects. Furthermore,the present disclosure may take the form of a computer program productthat is implemented on one or more computer readable medium (including,but not limited to, magnetic disk storage, CD-ROM and optical storage)containing computer-executable instructions.

What is claimed is:
 1. A method comprising: reading filteringrequirements; acquiring description information included in eachfiltering requirement; performing syntax analysis of the acquireddescription information to check whether the acquired descriptioninformation is valid; transforming all or-operations included in theacquired description information into one or more logical conjunctionoperations; listing description values of the filtering requirements toestablish an attribute description network, the attribute descriptionnetwork being a layered network, a respective layer corresponding to arespective attribute field, the respective attribute field having atleast one description value, layers of the attribute description networkhaving a hierarchical relationship from high to low level; readingdescription information of a data object to be filtered; extracting,from the description information of the data object, description valuesincluding at least one description value that is in the attributedescription network; reducing data computational amount by: establishinga mapping relationship between the filtering requirements and theattribute description network; generating a path dependency graphaccording to the mapping relationship; performing a traversal comparisonbetween the description values included in the description informationof the data object and description values in the path dependency graph,the traversal comparison including a depth-first traversal; and when thedescription information of the data object to be filtered does notinclude a description value, skipping traversal of description paths inthe path dependency graph that pass downward through the descriptionvalue.
 2. The method of claim 1, further comprising: during a process ofperforming the traversal comparison, recording a description path as amatching path of the data object in response to determining thatdescription values of the description path are included in thedescription information of the data object.
 3. The method of claim 2,further comprising determining, according to the matching path of thedata object, a filtering requirement that the data object meets.
 4. Themethod of claim 1, wherein the listing description values of thefiltering requirements to establish the attribute description networkincludes: classifying the acquired description information according toattributes, a corresponding attribute field being set for eachattribute, at least one piece of acquired description informationbelonging to each attribute being normalized and respectively used as atleast one description value under a respective attribute fieldcorresponding to a respective attribute; and hierarchically arrangingattribute fields according to the hierarchical relationship to form theattribute description network, a respective layer corresponding to therespective attribute field.
 5. The method of claim 4, wherein thehierarchically arranging the attribute fields according to thehierarchical relationship includes: acquiring a number of descriptionvalues under each of the attribute fields; and hierarchically arranging,in descending order of the numbers of description values under theattribute fields, the attribute fields in sequence according to thehierarchical relationship.
 6. The method of claim 4, wherein thehierarchically arranging the attribute fields according to thehierarchical relationship includes: acquiring, according to nature ofthe attribute fields, attribute fields in which a single descriptionvalue is to be selected; and placing, on top of other attribute fieldsin the hierarchical relationship, the attribute fields in which thesingle description value is to be selected, wherein an attribute fieldin which a single description value is to be selected refers to that,according to nature of the attribute field, description values includedin the attribute field are mutually exclusive.
 7. The method of claim 1,wherein in the attribute description network, different descriptionvalues of a same layer are arranged in sequence according to apredetermined sorting criterion.
 8. The method of claim 1, wherein theestablishing the mapping relationship between the filtering requirementsand the attribute description network to generate the path dependencygraph according to the mapping relationship includes: converting eachfiltering requirement into a description path expression form;respectively generating at least one description path of eachdescription path expression; acquiring non-duplicative description pathsof the filtering requirements to form a description path set; andmapping description paths in the description path set to the attributedescription network to form the path dependency graph.
 9. The method ofclaim 8, wherein the description path includes at least one descriptionvalue.
 10. The method of claim 8, wherein the description path includesa plurality of description values that that have conjunctionrelationships, different description values of a respective descriptionpath being located at different layers in the attribute descriptionnetwork, different description values being arranged in descending orderof levels of the different layers at which the description values arelocated.
 11. The method of claim 8, wherein the establishing the mappingrelationship between the filtering requirements and the attributedescription network to generate the path dependency graph according tothe mapping relationship includes: sorting the description paths basedon a sorting rule that a layer at a higher level has a higher priorityand a description value appearing first in a same layer has a higherpriority; mapping the description paths to the attribute descriptionnetwork in sequence according to a result of the sorting; and combiningparts that have completely identical high-layer description values inthe description paths to generate the path dependency graph.
 12. Themethod of claim 11, wherein the high-layer description values in thepath dependency graph are completely identical includes all layershaving identical description values starting downward from thehighest-layer description values included in the description paths. 13.The method of claim 1, further comprising: during a process ofperforming the traversal comparison, recording the description path as amatching path of the data object in response to determining that alldescription values of one description path are included in thedescription information of the data object; and determining, accordingto the matching path of the data object, a filtering requirement thatthe data object meets, the determining includes: determining, accordingto a description path expression form of a respective filteringrequirement, a description path included in the respective filteringrequirement; and determining that the data object meets the filteringrequirement, in response to determining that the description pathincluded in the respective filtering requirement is included in thematching path of the data object.
 14. The method of claim 13, whereinthe determining, according to the matching path of the data object, thefiltering requirement that the data object meets further includes:determining all filtering requirements that the data object meets. 15.The method of claim 14, further comprising classifying the data objectinto different categories according to the filtering requirements thatthe data object meets.
 16. An apparatus comprising: a filteringrequirement reading unit that reads filtering requirements; an attributedescription network establishment unit that lists description values ofthe filtering requirements to establish an attribute descriptionnetwork, the attribute description network being a layered network, arespective layer corresponding to a respective attribute field, therespective attribute field having at least one description value, layersof the attribute description network having a hierarchical relationshipfrom high to low level, the attribute description network establishmentunit including a description information acquiring sub-unit thatacquires description information included in each filtering requirement,performs syntax analysis of the acquired description information tocheck whether the acquired description information is valid, transformsall or-operations included in the acquired description information intoone or more logical conjunction operations; a data-object-to-be-filteredreading unit that reads description information of a data object andextracts, from the description information of the data object,description values including at least one description value that is inthe attribute description network; a path dependency graph generatingunit that reduces data computational amount by establishing a mappingrelationship between the filtering requirements and the attributedescription network, and generating a path dependency graph according tothe mapping relationship; and a traversal comparison unit that performsa traversal comparison including a depth-first traversal between thedescription values of the data object and description values in the pathdependency graph, during a process of performing the traversalcomparison, records a description path as a matching path of the dataobject in response to determining that description values of thedescription path are included in the description information of the dataobject, and when the description information of the data object to befiltered does not include a description value, skipping traversal ofdescription paths in the path dependency graph that pass downwardthrough the description value.
 17. The apparatus of claim 16, furthercomprising: a filtering requirement determining unit that determines,according to the matching path of the data object, a filteringrequirement that the data object meets.
 18. One or more memories storedthereon computer-executable instructions, executable by one or moreprocessors, to cause the one or more processors to perform actscomprising: reading filtering requirements; acquiring descriptioninformation included in each filtering requirement; performing syntaxanalysis of the acquired description information to check whether theacquired description information is valid; transforming allor-operations included in the acquired description information into oneor more logical conjunction operations; listing description values ofthe filtering requirements to establish an attribute descriptionnetwork, the attribute description network being a layered network, arespective layer corresponding to a respective attribute field, therespective attribute field having at least one description value, layersof the attribute description network having a hierarchical relationshipfrom high to low level; reading description information of a data objectto be filtered; extracting, from the description information of the dataobject, description values including at least one description value thatis in the attribute description network; establishing a mappingrelationship between the filtering requirements and the attributedescription network to generate a path dependency graph according to themapping relationship; performing a traversal comparison between thedescription values of the data object and description values in the pathdependency graph, the traversal comparison including a depth-firsttraversal; and when the description information of the data object to befiltered does not include a description value, skipping traversal ofdescription paths in the path dependency graph that pass downwardthrough the description value.
 19. The one or more memories of claim 18,wherein the acts further comprise: during a process of performing thetraversal comparison, recording a description path as a matching path ofthe data object in response to determining that description values ofthe description path are included in the description information of thedata object; and determining, according to the matching path of the dataobject, a filtering requirement that the data object meets.
 20. The oneor more memories of claim 18, wherein the listing description values ofthe filtering requirements to establish the attribute descriptionnetwork includes: classifying the acquired description informationaccording to attributes, a corresponding attribute field being set foreach attribute, at least one piece of acquired description informationbelonging to each attribute being normalized and respectively used as atleast one description value under a respective attribute fieldcorresponding to a respective attribute; and hierarchically arrangingattribute fields according to the hierarchical relationship to form theattribute description network, a respective layer corresponding to therespective attribute field.